The reproducibility of the coating properties is the result of an efficient control of the thermal spray process. Actually, it is not possible for the sprayer to guarantee the temporal reproducibility of the coating properties without online control. However, adjusting the system fluctuations with regards to the temperature, velocity and size of particle could alter some properties that depend or not on the in-flight particle characteristics. This study aims at discussing the existing correlations between the processing parameters and the coating properties established with a Neural Network methodology. It demonstrates the segmentation of the correlations by comparing the result of the merging procedure of two sub-network structures and the direct correlation from the processing parameters to the coating properties. The sub-structures are built considering respectively the in-flight particle characteristics relationship with the operating conditions and the in-flight particle characteristics relationship with the coating properties.